Annals of Telecommunications最新文献

While an increasing number of telecommunications firms are adopting green innovation (GI), research on the conditions under which innovation and collaboration decisions are made is still lacking. This paper proposes a mathematical model integrating innovation level, trust, and knowledge investment dimensions. Innovation and collaboration behaviors are discussed under various scenarios. A simulation is conducted with an evolutionary game theory approach to observe the effect of different parameters on innovation formation. The simulation analysis presents the optimal strategies for each scenario. Research on the green innovation behaviors of telecom operators and the impact of innovation strategies on operations and revenue have reference significance for telecom operators when it comes to selecting favorable innovation strategies, finding suitable partners and forming a relatively stable cooperative relationship in the industrial ecosystem.

In this paper, a scalable user-centric HC-RAN is taken into consideration, where each remote radio head (RRH) serves user equipments (UEs) over the same time/frequency resources by using time division duplex (TDD) mode. Network scalability results in the front-haul load and computational complexity at the baseband unit (BBU) pool remaining constant irrespective of the number of UEs in the network. During the channel estimation phase, each RRH will acquire the channel state information (CSI) based on the received pilot signals from the UEs. With the available CSI, each RRH will decode/precode the desired UE information in uplink and downlink, respectively. However, in ultra-dense networks, pilot contamination is a major limitation that hugely impacts the system’s performance. To address this, we proposed an uplink pilot power optimization algorithm by considering the inter-user interference due to pilot sharing and RRH selection. In this algorithm, the pilot power coefficients are designed in such a way as to decrease the mean square error (MSE) of the channel estimates. To achieve this, we used the successive convex approximation method. Moreover, we derived a closed-form expression for achievable spectral efficiency (SE) per UE, which will be valid for any pilot/data power optimization and RRH selection scheme. The results show that the proposed algorithm significantly improves the system performance in the channel estimation phase and will be more suitable for urban environments.

The sensor nodes in a wireless sensor network are equipped with a limited amount of energy. It is therefore necessary to ensure that the network’s lifespan is extended through efficient use of energy. Using cluster-based routing in wireless sensor networks is one of the most effective ways to deal with energy issues and improve the lifetime of the network. In this paper, an energy-efficient cluster-based routing protocol named Cluster Routing Protocol for Heterogeneous Network (CPHN) is proposed. The proposed CPHN makes use of the initial and residual energy levels of the nodes to select the most energy-efficient node as the cluster head, allowing the wireless sensor network to last longer. The proposed scheme uses the CH selection probability, residual energy, and initial energy of nodes to select the appropriate node as the CH. The simulation result shows that the proposed protocol outperforms various existing clustering protocols in terms of network lifetime, throughput, and stability period.

The advent of new computing and communication trends that link pervasive data sources and consumers, such as Edge Computing, 5G and IIoT, has led to the development of the Cloud-to-Edge Continuum in order to take advantage of the resources available in massive IoT scenarios and to conduct data analysis to leverage intelligence at all levels. This paper outlines the challenging requirements of this novel IoT context and presents an innovative IoT framework to develop dataflow applications for data-centric environments. The proposed design takes advantage of decentralized Pub/Sub communication and serverless nanoservice architecture, using novel technologies such as Zenoh and WebAssembly, respectively, to implement lightweight services along the Cloud-to-Edge infrastructure. We also describe some use cases to illustrate the benefits and concerns of the coming IoT generation, giving a communication performance comparison of Zenoh over brokered MQTT strategies.

The Internet of Things (IoT) is an emerging technology expected to play a significant role. The integration of IoT with cloud computing (CC) has enabled the creation of large-scale networks of interconnected smart devices and services. To provide optimal quality of service (QoS) for users, it is necessary to address the conflicting requirements of IoT services. The service selection problem is considered NP-hard and therefore requires using metaheuristic algorithms for efficient resolution. This paper presents a novel hybrid multi-objective metaheuristic, pRTMNSGA-III, which combines the strengths of RNSGA-III and TMNSGA-III to generate solutions that meet user preferences and eliminate unfavorable ones. To further optimize computational time, a parallel solution evaluation approach is employed. In addition, a more effective fuzzy membership function is proposed to select the best solution based on the requester’s preferred QoS. The proposed algorithm is evaluated on multiple datasets, and the results demonstrate its superiority over existing state-of-the-art algorithms, including RNSGA-III, TMNSGA-III, NSGA-III, pNSGA-II, NSGA-II, and NSPSO Experimental results demonstrate that pRTMNSGA-III outperforms existing algorithms by up to 37% in terms of the number of non-dominated solutions generated.

In this article, we implemented a novel blockchain-oriented RAN (BRAN) by allowing multiple players to trade RAN utilities (such as infrastructure) in terms of virtual network functions (VNFs) that are autonomous and dynamic. Particularly, we designed a multi-player network sharing (MPNS) smart contract which enables the automation of RAN-sharing processes using static or free-marketplace-oriented paradigms. The simulation results, acquired through auction-based and free-marketplace RAN-sharing methods, were evaluated based on user equipment (UE) capacity, UE satisfaction rate, base station (BS) efficiency, and end-to-end latency parameters. These results were then compared to those of the existing static RAN. It is observed from the simulation results that the performance of the blockchain-oriented free-marketplace RAN-sharing mechanism is 35% more efficient in terms of UE capacity and 40.5% more efficient in terms of UE satisfaction rate when compared to existing static RAN with the increase as the number of players in RAN environments. The proposed BRAN paradigm has spacious applications in 6G wireless networks, where user’s security, capacity, satisfaction rate, and latency are crucial constraints.